Fabrication and characterization of laminated SiC composites reinforced with graphene nanoplatelets

Nanosized allotropes of carbon have been attracting a lot of attention recently, but despite the steady growth of the number of scientific works on materials based on graphene family, there is still much to be explored. These two-dimensional carbon materials, such as graphene nanoplatelets, multilayer graphene or few layer graphene have emerged as a possible second phase for reinforcing ceramics, resulting in remarkable properties of these composites. Typically, graphene ceramic matrix composites are prepared by a colloidal or a powder route followed by pressure assisted sintering. Recently other traditional ceramic processes, such as tape casting, were also successfully studied. The aim of this research is to fabricate ce-SiC multi-layer composites containing 2, 4 and 8 vol% of graphene nanoplatelets (GNP) by tape casting and study the effect of these additions on the mechanical behavior of the composites. In order to achieve this purpose, samples were pressureless sintered and tested for density and mechanical properties. The elastic modulus was measured by the impulse excitation of vibration method, the hardness by Vickers indentation and fracture toughness using micro Vickers indentation and by three-point bending applying the pre-cracked beam approach. Results showed that up to 4 vol%, the density and mechanical properties were directly proportional to the amount of GNP added but showed a dramatic decrease for 8 vol% of GNP. Composites with 4 vol% of GNP had a 23% increment elastic modulus, while the fracture toughness had a 34% increment compared to SiC tapes fabricated under the same conditions. Higher amounts of GNP induces porosity in the samples, thus decreasing the mechanical properties. This study, therefore, indicates that 4% is an optimal amount of GNP and suggests that excessive amounts of GNP are rather detrimental to the mechanical properties of silicon carbide ceramic materials prepared by tape casting. (C) 2016 Elsevier B.V. All rights reserved.